ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-9-3409-2009Process-based modelling of biogenic monoterpene emissions combining production and release from storageSchurgersG.1ArnethA.12HolzingerR.3GoldsteinA. H.41Lund University, Department of Physical Geography and Ecosystems Analysis, Sölvegatan 12, 223 62 Lund, Sweden2University of Helsinki, Department of Physical Sciences, Helsinki, Finland3Utrecht University, Institute for Marine and Atmospheric Research, Utrecht, The Netherlands4University of California at Berkeley, Department of Environmental Science, Policy and Management, Berkeley, CA, USA2705200991034093423This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from http://www.atmos-chem-phys.net/9/3409/2009/acp-9-3409-2009.htmlThe full text article is available as a PDF file from http://www.atmos-chem-phys.net/9/3409/2009/acp-9-3409-2009.pdf

Monoterpenes, primarily emitted by terrestrial vegetation, can
influence atmospheric ozone chemistry, and can form precursors for
secondary organic aerosol. The short-term emissions of monoterpenes
have been well studied and understood, but their long-term
variability, which is particularly important for atmospheric
chemistry, has not. This understanding is crucial for the
understanding of future changes.
<br><br>
In this study, two algorithms of terrestrial biogenic monoterpene
emissions, the first one based on the short-term volatilization of
monoterpenes, as commonly used for temperature-dependent emissions,
and the second one based on long-term production of monoterpenes
(linked to photosynthesis) combined with emissions from storage, were
compared and evaluated with measurements from a Ponderosa pine
plantation (Blodgett Forest, California). The measurements were used
to parameterize the long-term storage of monoterpenes, which takes
place in specific storage organs and which determines the temporal
distribution of the emissions over the year. The difference in
assumptions between the first (emission-based) method and the second
(production-based) method, which causes a difference in upscaling from
instantaneous to daily emissions, requires roughly a doubling of
emission capacities to bridge the gap to production capacities. The
sensitivities to changes in temperature and light were tested for the
new methods, the temperature sensitivity was slightly higher than that
of the short-term temperature dependent algorithm.
<br><br>
Applied on a global scale, the first algorithm resulted in annual
total emissions of 29.6 Tg C a<sup>&minus;1</sup>, the second algorithm
resulted in 31.8 Tg C a<sup>&minus;1</sup> when applying the correction
factor 2 between emission capacities and production
capacities. However, the exact magnitude of such a correction is
spatially varying and hard to determine as a global average.